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- W3121429893 abstract "Unbalanced mixed linear models that contain a single set of random effects are frequently employed in animal breeding applications, in small-area estimation, and in the analysis of comparative experiments. The problem considered is that of the point or interval prediction of the value of a linear combination of the fixed and random effects or the value of a future data point. A common approach is BLUP (best linear unbiased prediction), in which an estimate of the variance ratio is regarded as the true value. Empirical BLUP is satisfactory-or can be made satisfactory by introducing appropriate modifications-unless the estimate of the variance ratio is imprecise and is close to zero, in which case more sensible point and interval predictions can be obtained by adopting a Bayesian approach. Two animal breeding examples are used to illustrate the similarities and differences between the Bayesian and empirical BLUP approaches." @default.
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- W3121429893 date "1992-12-31" @default.
- W3121429893 modified "2023-09-27" @default.
- W3121429893 title "Classical and Bayesian Prediction As Applied to an Unbalanced Mixed Linear Model" @default.
- W3121429893 hasPublicationYear "1992" @default.
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